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Phylogenetic distance does not predict competition
in green algal communities
H. R. NAUGHTON,1,3, M. A. ALEXANDROU,2 T. H. OAKLEY,2
AND
B. J. CARDINALE1
1
School of Natural Resources & Environment, University of Michigan, Ann Arbor, Michigan 48109 USA
2
Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara,
Santa Barbara, California 93106 USA
Citation: Naughton, H. R., M. A. Alexandrou, T. H. Oakley, and B. J. Cardinale. 2015. Phylogenetic distance does not
predict competition in green algal communities. Ecosphere 6(7):116. http://dx.doi.org/10.1890/ES14-00502.1
Abstract. Biologists have held the tenet that closely related species compete more strongly with each
other than with distant relatives since 1859, when Darwin observed that close relatives seldom co-occur in
nature and suggested it was because they competitively exclude one another. The expectation that close
relatives experience greater competition than distant relatives has become known as the ‘‘competitionrelatedness hypothesis (CRH).’’ The CRH is predicated on the assumption that closely related species are
more likely to have similar resource requirements than distant relatives, and thus, compete more strongly
for limited resources. While this assumption has been popular because it is intuitive, it has also been subject
to relatively little experimentation. Over the past decade, a growing number of CRH studies have arrived
at divergent conclusions showing that the strength of competitive interactions can increase, decrease, or be
independent of evolutionary relatedness. Most of these studies have focused on measuring competition
among species pairs as opposed to competition experienced by species when part of whole communities.
We tested whether the CRH holds in communities where individual species experience interactions with a
variety of other taxa, which we call the ‘resident community’. We performed a laboratory mesocosm study
using communities of eight species of freshwater green algae whose evolutionary relationships were
quantified using a recently developed multi-gene molecular phylogeny of 59 North American green algae.
We grew species alone and in various combinations in polyculture so that we could measure each species’
sensitivity to competition (reduction in intrinsic growth rate when grown alone vs. with a resident
community), relative yield, and competitive release (proportional change in biomass of a species when
grown in a resident community missing one competitor vs. in a community with all possible competitors).
While each of these metrics consistently revealed a prevalence of competitive interactions among the algal
species, none were predicted by the relatedness of a species to a resident community. This suggests that the
results of prior pairwise studies refuting the competition-relatedness hypothesis for green algae can be
extended to larger resident communities in which more complex ecological interactions possibly occur.
Key words: community ecology; competition; competition-relatedness hypothesis; competitive release; indirect
interactions; relative yield; sensitivity.
Received 10 January 2015; revised 23 February 2015; accepted 4 March 2015; final version received 8 April 2015;
published 21 July 2015. Corresponding Editor: D. P. C. Peters.
Copyright: Ó 2015 Naughton et al. This is an open-access article distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited. http://creativecommons.org/licenses/by/3.0/
3
Present address: Department of Environmental Earth System Science, Stanford University, Stanford, California 94305
USA.
E-mail: [email protected]
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al. 2014). Recent advances in genomic tools and
phylogenetic construction have allowed researchers to develop more quantitative metrics for
measuring species relatedness, such as phylogenetic distance (PD) that measures branch lengths
between taxa on a molecular phylogeny (Faith
1992, Webb 2000). Competition in most studies
has been measured as the reduction in biomass
or population growth rate of a focal species when
in the presence of another species relative to
when the focal species is grown alone in
monoculture (Gough et al. 2001, Freckleton et
al. 2009). A few terrestrial plant studies have
supported the CRH by showing that the presence
of close relatives reduces the biomass, chance of
invasion, or presence of other species for California grasses (Strauss et al. 2006) and arbuscular mycorrhizal fungi ( Maherali and
Klironomos 2007). Select experiments performed
with microbes have similarly shown that the
abundance and invasion success (i.e., positive
growth of a species introduced at low density to
a community at equilibrium; Chesson 2000) of a
species decreases as its relatedness to the resident
community increases (Jiang et al. 2010, Violle et
al. 2011, Peay et al. 2012). Large PDs among cooccurring species have also been shown to
coincide with decreased community stability,
which was interpreted as evidence for weak
competition amongst distant relatives leading to
reduced compensatory dynamics (Venail et al.
2013).
While results from several studies are consistent with predictions of the CRH, an increasing
number of recent studies have produced contrasting results that call into question the
generality of this hypothesis and its assumptions.
For example, studies using microbial communities have concluded that PD cannot predict the
strength of competition or likelihood of coexistence for bacterial strains (Schoustra et al. 2012)
or freshwater green algae (Fritschie et al. 2013,
Narwani et al. 2013, Venail et al. 2014). A number
of studies have shown no relationship between
the reduction in biomass of vascular plants
grown with competing species and the PD
between them for wetland herbaceous species
(Cahill et al. 2008), central European flowering
plants (Dostál 2011), French alpine trees (Kunstler et al. 2012) and Canadian grassland species
(Bennett et al. 2013). One animal field study
INTRODUCTION
Ever since Darwin (1859) proposed that closely
related genera tend not to coexist in the same
geographic region, ecologists have embraced the
idea that evolutionarily close relatives compete
more strongly than distant relatives. This hypothesis, which is now commonly referred to as
the competition-relatedness hypothesis (CRH;
Cahill et al. 2008), stems from the presumption
that closely related species are more likely to
share similar morphological, physiological, and
behavioral traits due to shared ancestry (Harvey
and Pagel 1991, Peterson et al. 1999, Blomberg et
al. 2003). The sharing of traits (many of which
may influence ecological interactions) among
closely related species is called ‘‘phylogenetic
niche conservatism’’ (Wiens and Graham 2005)
or ‘‘phylogenetic signal’’ (Losos 2008), depending
on the extent of departure of species trait values
from those predicted based on phylogenetic
relationships. If traits determining competitive
ability have more similar values for close
relatives than for distant relatives, then phylogenetically grouped species would be expected to
experience more competition with each other
than with distant relatives due to similar ecological requirements. Stronger competition among
close relatives could then result in exclusion of
the inferior competitor, unless the different
species diverge and evolve ecologically distinct
niches (Darwin 1859, MacArthur and Levins
1967, Losos et al. 2003). The intuitive hypothesis
that closely related species are more ecologically
similar and compete strongly (where species that
do not evolve niche differences face local
extinction) has led many biologists to propose
that understanding evolutionary history is critical for predicting community dynamics and the
composition of species in natural communities
(Brooks and McLennan 1991, Harvey and Pagel
1991, Webb et al. 2002, Cavender-Bares et al.
2009).
Over the past decade, there has been an
increase in the number of studies that have
directly manipulated the relatedness of species in
a community and then measured the strength of
competitive interactions (experiments compiled
by Cahill et al. 2008, Jiang et al. 2010, Dostál 2011,
Violle et al. 2011, Peay et al. 2012, Best et al. 2013,
Fritschie et al. 2013, Narwani et al. 2013, Venail et
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found that PD did not predict competition
strength between North American marine amphipods (Best et al. 2013). The lack of support for
the CRH is often presumed to represent a
violation of the assumption that ecological traits
are conserved across a phylogeny (Losos 2008,
Pearman et al. 2008) and, in fact, several studies
suggest that the biological traits that underlie
competition can be phylogenetically labile (Losos
2008, Savage and Cavender-Bares 2012, Sternberg and Kennard 2014; A. Narwani et al.,
unpublished manuscript).
Even though competition-relatedness experiments have grown in number and breadth of
study systems over the past decade, studies have
largely measured competition between just two
individuals or between two species’ populations
(but see Jiang et al. 2010, Dostál 2011, and Best et
al. 2013 for exceptions). Pairwise interaction
studies are the most common means to measure
competition because they facilitate direct observation of competitive effects of one species on
another (Cahill et al. 2008) and allow for
modeling of competition coefficients (Narwani
et al. 2013). However, extrapolation of pairwise
competitive interaction strengths to communitywide competitive outcomes is tenuous at best
(Chesson 2000, Narwani et al. 2013). This is
partly because more complex forms of interaction
such as indirect and intransitive interactions can
mask the magnitude and even the sign (i.e.,
competition versus facilitation) of pairwise interactions in multi-species communities (Strauss
1991, Wootton 1994, Valiente-Banuet and Verdu
2008, Martorell and Freckleton 2014). A number
of studies have empirically confirmed the presence of indirect and intransitive competition in
multispecies communities (Connell 1983, Schoener 1983, Keddy and Shipley 1989, Castillo et al.
2010). This supports theoretical predictions that
pairwise competition coefficients don’t predict
population dynamics a priori for communities of
three or more competing species (May and
Leonard 1975). Thus, in order to assess how PD
relates to competition in multi-species communities, it may be necessary to study multi-species
communities directly as opposed to inferring
community-wide competitive interactions from
pairwise combinations of the component species.
Here we report the results of an experiment in
which we measured the strength of competition
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in multi-species communities of freshwater green
algae. In order to assess whether PD determines
the level of competition experienced by members
of a multi-species community, we ran a laboratory mesocosm experiment in which we varied
the PD represented by eight common species of
green algae, and then assessed the competitive
response of each species to additions or deletions
of the other taxa grown in polyculture. We used a
data-rich molecular phylogeny of 59 green algae
species (Alexandrou et al. 2015) to determine the
relatedness of algal species comprising each
community. We measured phylogenetic distance
from a focal species to the resident community as
the average PD between a focal species and each
other species present in the community. Average
PD estimates were considered with and without
weighting by the resident species’ relative abundances to account for the possibly disproportionate impacts of dominant species on interactions.
We additionally measured PD between the focal
species and most closely related taxon and
between the focal species and a specific competitor for several analyses. We measured competition in three ways: First, we calculated the
‘sensitivity’ of a focal species to competition as
the change in growth rate of the focal species
when introduced at low density to a resident
community of seven other species relative to
growth of the focal species when alone in
monoculture (Chesson 2000). Second, we calculated the ‘relative yield’ of biomass of a focal
species grown in polyculture relative to monoculture. Competition from other species in the
polyculture depresses the focal species’ biomass
and results in relative yields less than unity.
Finally, we calculated ‘competitive release’ as the
biomass of a focal species when grown without
one competitor relative to when grown with a
suite of seven potential competitors in the full
resident community. The absence of a competitor
results in higher biomass of the focal species and
a competitive release greater than unity. The
concurrent analysis of relative yield and competitive release allowed us to search for phylogenetic signal of competitive response to a whole
community alongside competitive response to
each individual species removed from the community. In accordance with the CRH, we
predicted that species more distantly related to
members of the resident community would
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experience less competition than species more
closely related to the resident community. While
species experienced a range from no competition
to complete competitive exclusion, no measure of
competition could be explained by a species’
relatedness to its community.
MATERIALS
AND
Gottingen, Germany) culture collections.
Calculating phylogenetic distance
To estimate phylogenetic distances (PDs)
among species, we relied on a new phylogeny
for green algae (Alexandrou et al. 2015). The
phylogeny was constructed using Illumina transcriptome sequencing technology and the Osiris
pipeline for phylogenetics in Galaxy (Oakley et
al. 2014). This data-rich framework represents a
significant step forward from previous approaches that rely on single genes for estimates of
evolutionary relatedness. We used a multiple
sequence alignment of 119 genes (totaling 19,949
amino acids for 59 species of green algae) to
construct a maximum likelihood phylogeny with
RAxML, version 7.2.8 (Stamatakis et al. 2008).
The phylogeny was tested for topological robustness using 100 non-parametric bootstrap replicates. We calculated pairwise PDs (Faith 1992)
using the mean branch lengths connecting each
species pair (ignoring the root branch) using PD
pairs as implemented in Osiris (Oakley et al.
2014).
The pairwise PDs were used to calculate three
complementary metrics of relatedness between a
species and a resident community: nearestneighbor phylogenetic distance (NPD), average
phylogenetic distance between a species and all
members of the community that is not weighted
by abundance (‘‘unweighted’’ phylogenetic distance, UPD), and average phylogenetic distance
between a focal species and all other species in
the community weighted by the relative abundance of each other species (‘‘weighted’’ phylogenetic distance, WPD). WPD between a focal
species i and the community was calculated as
follows: biomass values for each species were
converted to a proportion of total community
biomass. Pairwise PD between the focal species, i,
and any other species in the community k 6¼ i,
was multiplied by the biomass fraction of k.
These abundance-weighted pairwise PD values
between a focal species and every other species
present in the community were then summed to
obtain the weighted average PD between that
focal species and the community.
Because concurrent analyses using UPD and
WPD emphasize how conclusions are influenced
by the dominance of resident species in a
community (Goldberg and Fleetwood 1987, Ca-
METHODS
Species selection and culture
This experiment focused on eight species of
freshwater green algae from different genera
within the Chlorophyta and Charophyta. The
Chlorophytes included Chlorella sorokiniana, Closteriopsis acicularis, Pandorina charkowiensis, Scenedesmus acuminatus, Selenastrum capricornutum,
and Tetraedron minimum. The Charophytes included the two desmids Cosmarium turpinii and
Staurastrum punctulatum. According to the U.S.
Environmental Protection Agency National Lake
Assessment (U.S. Environmental Protection
Agency 2007), all eight taxa rank among the
top 50% of the most abundant freshwater green
algal genera out of 429 taxa found in North
American lakes (Venail et al. 2014), and all but
one pair of genera (i.e., Pandorina and Tetraedron)
co-occur in lakes throughout the continental USA
(Appendix C: Table C1). An 8-species pool falls
on the lower end of the levels of algal diversity
that are found in natural lakes, though it is
within 1 SD of the mean (Appendix C: Fig. C1).
Aside from their ecological relevance, these eight
species were selected based on their ability to be
cultured in laboratory conditions using common
growth media (COMBO; Kilham et al. 1998) and
based on their morphological differences, which
allowed for visual identification of unique
species during the cell counting process. These
eight taxa were also included in a new multigene molecular phylogeny of 59 North American
freshwater green algae that provides estimates of
phylogenetic relatedness based on an unprecedented level of genetic sampling (Alexandrou et
al. 2015). This phylogeny provides a good
framework for relating ecology to phylogenetic
relationships because the phylogeny predominantly comprises readily available, culturable
algae. All species cultures were supplied from
either the University of Texas Culture Collection
of Algae (UTEX; Austin, Texas, USA) or the
Sammlung von Algenkulturen Gottingen (SAG;
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hill et al. 2008), we present results for both
throughout this paper. NPD should, in principle,
more accurately predict competition than community-averaged PDs if competition between
close relatives is sufficiently strong that the
nearest neighbor’s effect on a focal species
dominates over other competitive interactions
(Castillo et al. 2010). However, the same three
species (S. acuminatus, C. sorokiniana, and C.
acicularis) often dominated the community biomass irrespective of values of PD. Unless the
nearest neighbor of the focal species happened to
be one of those dominant species, the nearest
neighbor represented a small fraction of community biomass and likely did not strongly affect the
focal species’ growth. Because the results of
analyses using NPD were qualitatively similar
to other analyses, and because NPD measures
distance from competitors with vastly different
biomasses; analyses using NPD are included
only in Appendix B.
species polyculture treatment included nine
replicate bottles of all eight species grown
together, totaling nine bottles.
All treatments were inoculated at 800 cells/mL
total density in the 1-L bottles. Species in
polyculture were inoculated as a replacement
series at either 114 (invasion treatments) or 100
(full polyculture treatment) cells/mL. Beginning
on the fourth day of the experiment (DOE 4),
10% of the media was replaced in a semicontinuous fashion at the same time every other
day using peristaltic pumps (MasterFlex L/S
Multichannel Pump, Cole-Parmer, Vernon Hills,
Illinois, USA). Two milliliters of exchanged
experimental media were retained for sampling
after each media exchange. One-milliliter samples of removed media were fixed with 250 lL
10% formalin (Fisher Scientific, Pittsburgh, Pennsylvania, USA) and stored in the dark until
further processing. One mL samples of removed
media were directly pipetted into 48 multiwell
tissue culture plates (Becton Dickinson Labware,
Franklin Lakes, New Jersey, USA) for in-vivo
chlorophyll-a fluorescence readings (460/685 nm
excitation/emission wavelengths, measured on a
Synergy H1 Hybrid Reader [BioTek, Winooski,
Vermont, USA]) to monitor the growth of algal
communities and determine when bottles had
reached steady-state biomass. Steady-state biomass was recognized as a saturating response in
natural-log transformed fluorescence reads over
time. We accepted a non-significant increase in
ln(fluorescence) between any two consecutive
exchange days between DOE 20 and DOE 26 as
evidence of steady-state in order to inoculate
invaders prior to population crashes or secondary exponential growth phases. Once all sevenspecies invasion treatment polycultures reached
stable equilibrium (DOE 26), the eighth ‘‘invader’’ species was inoculated into each invasion
treatment bottle at 800 cells/mL (Fig. 1). All
bottles continued to receive media exchange and
were sampled for twelve days post-invasion.
Experimental setup and protocol
Three treatments representing a sum 81 experimental units were set up in an environmental
chamber and grown over the course of 38 days
(Fig. 1). The experimental units were 1-L Pyrex
glass bottles filled with 1 L modified COMBO
growth medium (Kilham et al. 1998). Experimental units were all placed in a walk-in environmental growth chamber that was kept at 208C
with a 16/8 h alternating light/dark cycle implemented using 28-W fluorescent lamps (Portable
Luminaire, Underwriter Laboratories, Research
Triangle Park, North Carolina, USA) emitting a
mean 82 lmolm2sec1 of photosynthetically
active light (measured using an Apogee Instruments Quantum light meter, Logan, Utah, USA).
Bottles were placed in randomly selected positions on tissue culture roller racks (120 V Roller
Apparatus, Wheaton, Millville, New Jersey, USA)
that rotated at 5 rpm, which was fast enough to
ensure continuous suspension of cells and allow
for even light exposure. Monoculture treatments
included three replicates of each of the eight
species grown alone, totaling 24 bottles. Eight
‘‘invasion’’ treatments were set up with each
possible seven-species combination grown to
steady state biomass, followed by invasion by
the eighth species (8 treatments 3 6 replicate
bottles each ¼ 48 bottles total). A full eightv www.esajournals.org
Data analysis
Cell counts were performed to estimate species
density over the course of the experiment, which
was then used to compute metrics of competition. Ten-microliter aliquots of preserved samples
were counted on a compound light microscope at
1003 and 4003 magnification using a hemacy5
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Fig. 1. Diagram of experimental setup including experimental treatments, measurements taken from each
treatment and an example of the growth dynamics for each treatment over time. Each colored dot represents one
of eight species and each cylinder represents a 1-L bottle. Dot size indicates cell density, where large dots
represent steady-state biomass. Eight Invasion treatments were used in this experiment, but only one example is
drawn in the row labelled ‘‘Invasion Treatments’’ due to limited space. The final column lists all measurements
taken from algal growth curves to estimate competition. The lower panel shows how growth curves were used to
measure (a) slope ¼ rmax, maximum intrinsic growth rate of a species in monoculture, (b) Mi,1, steady-state density
of species i in a 1-species monoculture, (c) slope ¼ rinv, maximum intrinsic growth rate of a species as an invader,
(d) Mi6¼ j,7, steady-state density of species i 6¼ j in a 7-species resident community where j represents the absent
species, and (e) Mi,8, steady-state density of species i in full polyculture of 8 species. All densities (b, d, e) were
converted to biomass values for further analysis. Note: graphs are examples and do not use experimental data.
(lgL1) by assuming that cells are primarily
composed of water, which has a relative density
of 1.
Growth curves of cell density over time were
plotted for each monoculture bottle over the
course of the entire experiment and for the
invader species in each invasion bottle over the
tometer. Algal biomass was approximated by
multiplying cell density by species-specific cell
volume, which was measured from 10 cells of
each species culture used in the experiment on a
Benchtop FlowCam (Fluid Imaging Technologies, Scarborough, Maine, USA). Biovolumes
(lm 3L1) were then converted to biomass
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twelve-day period following its introduction on
DOE 26 (Appendix A: Figs. A1, A2). Monoculture maximum intrinsic growth rates, rmax, and
invader growth rates when rare, rinv, were
calculated as the log ratio of density (D) on the
final and initial days of exponential growth
divided by number of days of exponential
growth (t); Eq. 1.
Dfin
=t:
ð1Þ
r ¼ ln
Dinit
combined competitive pressure from all species
present in its community. In contrast, competitive
release, or CR, compares the biomass of a species
grown in a community missing one member
versus in the full polyculture; Eq. 4. CR assesses
the extent to which competition experienced by a
focal species within an eight-species community
depends on specific pairwise competitive interactions. Thus, by including both RY and CR in
our analysis, we can learn whether PD effectively
predicts diffuse and/or species-specific competition strength.
The period of exponential growth was determined by maximizing the fit of linear regressions
to the log-transformed growth curves of each
bottle (Appendix A).
Maximum intrinsic growth rate and growth
rate when rare were used to calculate each
species’ sensitivity to competition as well as its
invasion success into an established community.
A given species’ sensitivity to competition, S, is
the reduction in its per-capita growth rate when
introduced at low density to a resident community relative to its per-capita growth rate in
monoculture; Eq. 2.
S ¼ ðrmax rinv Þ=rmax :
ð3Þ
CRij ¼ Mi6¼j;7 =Mi;8 :
ð4Þ
In Eqs. 3 and 4, M is the biomass of a focal
species i on DOE 26. Subscript j refers to the
species missing from the seven-species polycultures prior to invasion, ranging from 1 to 8 but
excluding j ¼ i. Subscripts 8, 1 and 7 refer to 8species polyculture, monoculture and 7-species
polyculture, respectively.
Statistical analysis
ð2Þ
Several data analyses were performed to
address whether PD predicts competitive outcomes in a multispecies community using R,
version 2.15.2 (R Development Core Team 2012).
First, we used linear regression to relate species’
sensitivities to competition, Eq. 2, to phylogenetic
distance, where we ran two separate analyses
using WPD and UPD as the independent
variable. Sensitivities were also analyzed using
a logistic regression to ask whether the likelihood
of invasion (1 ¼ successful, 0 ¼ unsuccessful)
increases with PD between a community and an
introduced species. WPD was the only PD metric
used for the logistic regression because it allowed
each replication to be used as an independent
data point as opposed to UPD or NPD, for which
every replicate of the same invader species had
an identical phylogenetic distance.
We then performed a linear regression of RY
against WPD and UPD to assess whether
phylogeny predicts how competition affects
equilibrium yields of species in a community.
RY values were natural log transformed to
normalize residuals. RY values were expected to
increase towards unity with increasing phylogenetic distance. In addition to the expectation that
As a given species’ growth rate when rare
approaches its maximum intrinsic growth rate,
the numerator in S approaches zero, signifying
low competitive pressure from the established
community to which the invader is introduced.
Sensitivities between zero and one signify competition even though the invader is able to
establish itself in the community. A sensitivity
of one indicates strong competition (complete
niche overlap) from other species in a resident
community. Sensitivities greater than one signify
invader mortality, as rinv would be negative,
indicating unsuccessful invasion.
Biomass of each species was determined for
each monoculture, invasion (7-species) and full
polyculture (8-species) bottle at stable equilibrium (DOE 26) for use in competition calculations
(Fig. 1). Biomass of species in 8-species (full)
polyculture was compared with their biomass in
monoculture and in 7-species polyculture to
calculate relative yield and competitive release,
respectively. Relative yield, or RY, is the biomass
of a species grown in polyculture relative to its
biomass in monoculture; Eq. 3. RY measures
competitive response of a focal species to the
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RYi ¼ Mi;8 =Mi;1
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Fig. 2. Invader sensitivity (S ) as a function of its phylogenetic distance to the resident community (A) and
invasion success of species introduced at low abundance to communities at equilibrium as a function of their
phylogenetic distance to the resident community (B). Sensitivity to competition is the reduction in intrinsic
growth rate of a species introduced at low density (i.e., ‘‘invader’’) to a polyculture at equilibrium relative to its
intrinsic growth rate in monoculture. S of each invading species, indicated by points labelled with the species’
abbreviated genus name, was analyzed as a function of abundance-weighted PD (WPD) and unweighted
average PD (UPD) between the invading species and all other members of a polyculture community. Points
below the dotted line at S ¼ 1.0 indicate species with positive growth-when-rare and points above the dotted line
indicate species with negative growth-when-rare. Error bars show standard error of S calculated for six replicate
mesocosms. Neither WPD nor UPD significantly predicted S (WPD: n ¼ 8, F ¼ 0.26, P ¼ 0.63; UPD: n ¼ 8, F ¼ 1.39,
P ¼ 0.28). Species with S , 1 were given an invasion success of 1 ¼ successful, and species with S . 1 were given
an invasion success of 0 ¼ unsuccessful (B). WPD between the invading species and the polyculture community
was not able to predict invasion success (n ¼ 48, Z ¼ 0.53, P ¼ 0.60).
the presence of a competitor will reduce the
biomass of a species (i.e., Eq. 3), the reverse
should also be true: the removal of a competitor
from a community should result in the release of
competition and hence a relatively larger biomass of any species left behind (i.e., competitive
release, Eq. 4). Assuming that competitive
interactions are stronger for close relatives, we
hypothesized that competitive release should
decrease as the PD between the focal species
and its removed competitor increases. This
hypothesis was assessed by linear regression of
CR of a focal species versus PD between the focal
and missing species, where a negative slope
would support the CRH. Though the regression
of CR against PD for each species might be
significant, the relationship for each species could
have a unique intercept and slope that when
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analyzed compositely would produce no significant trend. To account for species’ unique
responses to competitors, (which was shown by
the broad range of sensitivities of our eight algal
species, Fig. 2), we additionally looked for
relationships between CR and PD for each
species individually. Because P. charkowiensis
did not appear in any replicate for five invasion
treatments (probably due to competitive exclusion), nothing could be said about its competitive
release from these five species and only two
points appear in Fig. 4D.
RESULTS
Contrary to predictions of the competitionrelatedness hypothesis (CRH), we found no
relationship between a species’ sensitivity (S ) to
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Fig. 3. Relative yield (RY ) of a focal species in polyculture versus monoculture as a function of abundanceweighted PD (WPD, (A)), and unweighted PD (UPD, (B)), between the focal species and all other taxa in the
polyculture. Points are labelled with focal species names. RY values are natural log-transformed and standard
errors approximated as in Hedges et al. (1999). The dotted line at ln(RY ) ¼ 0 marks a relative yield of 1 after
transformation, which indicates equivalence of focal species biomass in polyculture and in monoculture. No
significant relationship was found (WPD: n ¼ 8, F ¼ 0.52, P ¼ 0.50; UPD: n ¼ 8, F ¼ 1.40, P ¼ 0.28).
interspecific competition and its relatedness to
other resident members comprising an algal
community. No significant trends were observed
in a linear regression of sensitivity versus
average abundance-weighted phylogenetic distance (WPD) or average unweighted phylogenetic distance (UPD; Fig. 2A). Using S . 1 as an
indicator of an unsuccessful invasion and S , 1
as an indicator of a successful invasion, phylogenetic distance also did not predict whether a
species introduced at low density could successfully invade a community at equilibrium in a
logistic regression of invasion success (positive
growth-when-rare) against WPD (Fig. 2B). The
lack of a significant relationship between PD and
invasion success was partly driven by the two
charophyte species (C. turpinii and S. punctulatum), which had the highest values of PD (the
species are more distantly related to the chlorophytes than chlorophytes are to each other), but
which were rarely able to invade resident
communities (invasion success ¼ 0). These results
indicate that whether sensitivity is interpreted as
a continuous metric of competition strength or
converted to a binary of successful/unsuccessful
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invasion, species’ PD to a community was not
related to these metrics of competition.
Relatedness to the community was also a poor
predictor of species relative yields (RYs) in 8species (full) polyculture versus in monoculture.
Seven out of eight species had RYs less than 1,
which suggests competition for limiting resources. However, there was no significant relationship between RY and WPD or UPD (Fig. 3). In
contrast to the other species, S. acuminatus had an
RY approximately equal to 1 (which after logtransformation is 0; Fig. 3), suggesting that S.
acuminatus was competitively dominant over the
other seven species used in this experiment.
Surprisingly, several species that had high RY
values (i.e., experienced low competition in
polyculture) also had high S values (i.e., were
highly sensitive to competition), and vice-versa.
For instance, S. punctulatum had the highest S
(Fig. 2A), meaning its growth rate was most
depressed by the presence of the other species,
but also the second-highest RY (Fig. 3), meaning
its steady-state biomass was largely unaffected
by the presence of other species relative to its
biomass in monoculture. S. capricornutum had the
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NAUGHTON ET AL.
Fig. 4. Competitive release (CR) as a function of phylogenetic distance between a focal species and the missing
competitor. CR is the yield of a focal species in a 7-species polyculture that is missing one competitor relative to
the yield of that same focal species in a full 8-species polyculture. Subplot labels refer to focal species and points
within each subplot are the first three letters of the genus of the missing competitor. For all linear regressions
(except that of P. charkowiensis, for which too few data points were recovered for linear regression), there was no
significant relationship (n ¼ 7, P . 0.24 for all). Each subplot, (A–H), corresponds to the relationship between PD
and competitive release experienced by C. sorokiniana (P ¼ 0.24), C. acicularis (P ¼ 0.71), C. turpinii (P ¼ 0.86), P.
charkowiensis, S. acuminatus (P ¼ 0.94), S. capricornutum (P ¼ 0.76), S. punctulatum (P ¼ 0.25), and T. minimum (P ¼
0.66), respectively. CR values are natural log transformed and error bars represent standard error calculated as in
Fig. 3. Points were jittered to improve visualization, but they retain their relative positions. The horizontal dashed
line at ln(CR) ¼ 0.0 corresponds to CR ¼ 1 after transformation.
F ¼ 0.32, P ¼ 0.57). In addition, there was no
relationship between CR and PD to the missing
species for any of the eight taxa when examined
individually (Fig. 4). Individual competitors
appeared to greatly impact the biomass of focal
species. In particular, the absence of S. acuminatus
led to a large CR in several focal species (Fig.
4A, B, G), while no single species greatly impacted the biomass of S. acuminatus (Fig. 4E). These
findings corroborate results in Fig. 3 that suggest
S. acuminatus was a superior competitor. Several
species showed CR values less than 1 (or less
than 0 after log transformation, Fig. 4), meaning
their biomass decreased when one competitor
was absent from the community. These cases
probably represent instances of facilitation by the
lowest S (Fig. 2A) and RY (Fig. 3) recorded,
making it the best and worst competitor according to each competition measure, respectively.
The difference between these two measures of
competition suggests that initial densities and
priority effects may have played a role in
determining algal community structure (Peay et
al. 2012).
PD between a focal species and a competitor
species was unrelated to the yield of the focal
species grown in a 7-species polyculture (without
the competitor) relative to in full 8-species
polyculture (with the competitor). There was no
significant relationship between competitive release (CR) and phylogenetic distance between a
focal species and the missing competitor (N ¼ 51,
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NAUGHTON ET AL.
absent species (Fritschie et al. 2013).
competition for the same species interacting in
multi-species communities. Regardless, we still
reached the same conclusion as previous experiments showing that no measure of competition
was significantly influenced by species relatedness. Rather than any general relationship of
competition to phylogenetic relatedness, particular species appeared to drive competition
strength across the community. Our study thus
extends the generality of past CRH results to
multi-species communities in which interactions
may be more complex and not readily predicted
from pair-wise interaction strengths.
The lack of any relationship between competition and PD suggests that the biological traits
that underlie competition in algae do not show
phylogenetic signal. While the traits determining
competitive outcomes for the green algal species
used in this experiment have yet to be identified,
a recent study showed that 13 out of 17 traits
related to nutrient uptake, stoichiometry and cell
morphology lack phylogenetic signal across a
phylogeny of 48 species inclusive of the eight
used in our experiment (A. Narwani et al.,
unpublished manuscript). Numerous other studies
have also found a lack of phylogenetic signal for
traits thought to underlie competitive interactions for other groups of organisms (Rheindt et
al. 2004, Cavender-Bares et al. 2006, Silvertown et
al. 2006b, Anderson et al. 2011, Savage and
Cavender-Bares 2012, Best and Stachowicz 2013).
Several hypotheses have already been proposed to explain the lack of signal between
competitive ability and phylogenetic distance in
prior studies (Cavender-Bares et al. 2009, Vamosi
et al. 2009, Mayfield and Levine 2010). One
possibility is phenotypic plasticity, where organisms can modify phenotypic expression depending on biotic and abiotic components of their
environment (Agrawal 2001). Species with highly
plastic ecological traits (i.e., intraspecific trait
variability is greater than interspecific variability)
can adopt new niches over time and reduce
interspecific competition (Miner et al. 2005).
Phenotypic plasticity could explain the lack of
phylogenetic signal found in our study since
certain types of algal traits are labile (Litchman et
al. 2012); but in contrast to this hypothesis, algal
trait averages often differ more strongly between
species than within species (Edwards et al. 2012).
Alternatively, rapid evolution of ecological char-
DISCUSSION
This experiment adds to a growing body of
literature that assesses whether closely related
species compete more strongly than distantly
related species—an idea now known as the
competition-relatedness hypothesis (CRH; Cahill
et al. 2008). Of the studies that have directly
measured competition strength, several have
supported the CRH (Valiente-Banuet and Verdu
2007, Jiang et al. 2010, Burns and Strauss 2011,
Violle et al. 2011, Peay et al. 2012). However, an
increasing number of recently published studies
have found that measures of competition at
different life stages lead to differing conclusions
about the validity of the CRH (Castillo et al. 2010)
or that there is no evidence for stronger
competition amongst close relatives (Cahill et
al. 2008, Dostál 2011, Best et al. 2013, Fritschie et
al. 2013, Narwani et al. 2013, Venail et al. 2014).
Thus, support for the CRH to date has been
mixed.
The competition experiments cited above have
trended towards comparing competition as a
function of phylogenetic distance among species
pairs. While there are numerous benefits of pairwise competition studies (Cahill et al. 2008),
interactions measured in pair-wise combinations
may or may not predict how relatedness affects
competition in more complex, multi-species
communities (Castillo et al. 2010). There is, in
fact, some reason to believe that the species used
in this study interact differently when they are in
multi-species communities. Evidence for this
comes from a comparison of our results to those
of a companion experiment in which Venail et al.
(2014) measured the sensitivity of species to
competition (S, just as in Eq. 2) for all pair-wise
interactions of the same eight species used here
(see Fig. 4, x-axis; Venail et al. 2014). When we
compared the values of S measured in our study
to those measured in Venail et al. (2014), we
found no significant correlation between the two
sets of measurements (R ¼ 0.51, N ¼ 8, P ¼ 0.20).
Of course, the lack of correlation could be due to
differences in methodologies among the two
experiments. But it could also indicate that the
strength of competition measured in pair-wise
interactions does not predict the strength of
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NAUGHTON ET AL.
acters can negate any relationship between
ecology and phylogenetic distance (Schluter
2000, Rheindt et al. 2004, Losos 2011). Rapid
trait evolution within a lineage—for instance,
through adaptive radiation—in traits important
to competition can result in close relatives that do
not compete strongly (Revell et al. 2008). Recent
evolution of competitive traits could account for
our finding no phylogenetic signal for competition. Several traits important for competition,
including those related to nitrogen uptake and
cell morphology, have evolved relatively recently
on the green algae phylogeny (A. Narwani et al.,
unpublished manuscript), suggesting rapid trait
evolution may be responsible for low phylogenetic signal amongst the algal species in this
study. Lastly, convergent evolution can produce
distantly related species that are ecologically
similar and potentially compete strongly—a
pattern that would oppose the CRH (CavenderBares et al. 2009, Mayfield and Levine 2010). The
key point here is that several distinct evolutionary and ecological scenarios could explain why
our results do not support the CRH.
As with any laboratory experiment, our study
system represents an oversimplification of nature
and, as such, certain caveats limit the extension
of these results to natural algal communities. The
relatively static environmental conditions that
included a semi-continuous supply of nutrients,
mixed (homogeneous) media, continuous light
exposure and lack of disturbances (other than
media exchanges) reduce spatial and temporal
heterogeneity relative to natural conditions. This,
in turn, may reduce niche opportunities and the
expression of different biological traits, forcing
competition to be more prominent in our system.
Alternatively, one could imagine competition
being more exaggerated in natural waters than
in the laboratory mesocosms for the same
reasons mentioned above—i.e., minimization of
variability in a given resource’s supply. For
instance, shallow moving waters may dissolve
gases more effectively than in our roller bottles
and thus remove the opportunity for species to
differentiate based on CO2 or O2 availability.
Additionally, natural processes such as dispersal
and herbivory—which are known to influence
species interactions (Cyr and Face 1993, Amarasekare et al. 2004)—were not included in our
experiment, and may limit the reproducibility of
v www.esajournals.org
our results in more natural algal communities.
Therefore, we caution against extrapolating
results from our study to natural lake ecosystems
without confirmation from field experiments.
Another potential criticism of our study is that
our species pool did not encompass the appropriate phylogenetic scale (Cavender-Bares et al.
2006, Silvertown et al. 2006a, Swenson et al. 2006,
Losos 2011). This criticism is commonly levied on
empirical tests of the CRH that fail to find
significant results, as it is often argued that
significant results might appear if the focal
species were more closely (e.g., Cavender-Bares
et al. 2006) or more distantly (e.g., considering an
entire genus’ niche for climate tolerance; Wiens
and Graham 2005) related. However, we do not
believe this criticism applies to our work. The
appropriate scale for testing the CRH is a scale at
which species interactions like competition are
prominent (Vamosi et al. 2009). Indeed, ‘‘scale’’
needs to be defined on the basis of the ecological
interaction one is trying to explain, and the
question is whether or not phylogenetic relationships are predictive of species interactions for the
species for which interactions occur. Competition
was prominent among the species used in our
study, with interaction strengths that ranged
from near zero (e.g., S. acuminatus; Fig. 3A) to
nearly complete competitive exclusion (e.g., P.
charkowiensis). These interactions spanned nearly
the entire range of what is possible for negative
interactions, and we would argue that this
continuum represents an appropriate template
to determine whether phylogenetic relationships
can explain variation in interaction strengths.
Researchers from many disciplines have been
attracted by the promise of a predictive relationship between evolutionary history and species’
ecology. For example, ecologists have used
phylogenies to infer patterns of community
assembly and the mechanisms that lead to
species co-occurrence (Webb et al. 2002). Conservation biologists have promoted using PD to
maximize the adaptability, resilience, and ecological function of ecosystems (Vane-Wright et al.
1991, Faith 1992, Strauss et al. 2006, Forest et al.
2007, Cadotte et al. 2008, Cadotte et al. 2009). The
fact that competitive ability is often unrelated to
phylogenetic distance for communities of microorganisms, plants and animals implies that the
traits underpinning species’ ecology are often not
12
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Anderson, T. M., J. Shaw, and H. Olff. 2011. Ecology’s
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Cadotte, M. W., B. J. Cardinale, and T. H. Oakley. 2008.
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Cavender-Bares, J., K. H. Kozak, P. V. Fine, and S. W.
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species meet the CRH assumption of phylogenetic signal of ecologically relevant traits, it may
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inferences and conservation decisions based
solely on the relatedness of species within a
community.
ACKNOWLEDGMENTS
We thank James Herrin, Keith Fritschie and Charlotte Wilson for technical assistance throughout the
experiment, and Anita Narwani and Celia Miller for
ecological and analytical insight. B. Cardinale, T.
Oakley, and H. Naughton designed the experiment.
H. Naughton performed the experiment. B. Cardinale
and H. Naughton analyzed the data and T. Oakley and
M. Alexandrou provided the phylogeny. All authors
contributed to the manuscript. This work was supported by the U.S. National Science Foundation’s
DIMENSIONS of Biodiversity program in a grant to
B. Cardinale (DEB-1046121) and to T. Oakley (DEB1046307). We acknowledge support from the Center
for Scientific Computing at the CNSI and MRL: an NSF
MRSEC (DMR-1121053) and NSF CNS-0960316. This
material is based upon work supported by the
National Science Foundation Graduate Research Fellowship under Grant No. DGE 1256260. Any opinion,
findings, and conclusions or recommendations expressed in this material are those of the authors and do
not necessarily reflect the views of the National Science
Foundation.
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ecology. Annual Review of Ecology and Systematics 33:475–505.
Wiens, J. J., and C. H. Graham. 2005. Niche conservatism: integrating evolution, ecology, and conservation biology. Annual Review of Ecology, Evolution,
and Systematics 36:519–539.
Wootton, J. T. 1994. Predicting direct and indirect
effects: an integrated approach using experiments
and path analysis. Ecology 75:151–165.
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SUPPLEMENTAL MATERIAL
APPENDIX A
growth rate over what appeared to be the full
exponential growth phase. Maximum intrinsic
growth rates (rmax) were calculated according to
Eq. 1 and appear in Fig. A1 as the slope of the
mean of the best least-squares fits to the logtransformed growth curves for the three replicate
bottles over points pertaining to exponential
growth phase.
The exponential growth phase of invaders in
the invasion treatments was determined to occur
over the linear portion of the invader’s natural
log-transformed growth curve (Fig. A2). Linear
portions of ln-transformed invader growth
curves were assessed visually. If no clear exponential phase existed (i.e., for all species except S.
capricornutum), the invader species were assumed
to still be in exponential growth (or decline) at
the end of the experiment. According to Eq. 1, the
log ratio of cell density between invader inoculation and the final day after introduction (12
days later) was used to calculate invader growth-
Monoculture and invader growth curves
and growth rate estimation
The exponential growth phase for monoculture
treatments was determined to occur over the
linear portion of the natural log-transformed
time-series of population cell densities (Fig. A1).
Linear portions of ln-transformed monoculture
growth curves were assessed visually, then
confirmed via the least-squares regression coefficient (multiple R 2) for the linear fit to the data
points thought to represent exponential growth
phase. While the highest multiple R 2 value was
taken to signify best fit, visual determination of
final day of exponential growth was used in
preference to R 2 values in cases: (1), when the
best linear fit included less than three data
points, and (2), when data points giving better
R 2 values due to inclusion or exclusion of
spurious points did not represent the intrinsic
Fig. A1. Growth curves for monoculture treatments. Each subplot shows the mean density of the three replicate
bottles for the species labelled above the plot, where the error bars represent standard error of the three replicates.
Slopes of the lines represent the maximum intrinsic growth rate, rmax, for each species when grown in
monoculture.
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Fig. A2. Growth curves of the ‘‘invader’’ species in the invasion treatments. Each subplot shows the density of
the invader, indicated by the subplot label, averaged over six replicate invader bottles. Error bars represent
standard error of the six replicates. Slopes of the lines represent invader maximum growth rate, rinv, after being
introduced to steady-state resident communities.
when-rare (rinv) for all species except S. capricornutum, in which case the sixth day after
introduction was considered its final day of
exponential growth.
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APPENDIX B
Nearest neighbor phylogenetic distance (NPD)
analyses
No measure of competition was significantly
related to a species’ phylogenetic distance to its
closest relative in a community. Sensitivity (S )
versus NPD gave a statistically non-significant
negative trend (Fig. B1A). Relative yield (RY )
also showed a non-significant negative trend
with NPD (Fig. B1B). Thus, both analyses
performed using NPD (the only measure of PD
used in this study based on statistically independent comparisons) do not support the CRH.
Fig. B1. Sensitivity, or S, (A) and relative yield, or RY,
(B) of a focal species versus the phylogenetic distance
between it and its closest relative in the community
(‘‘nearest neighbor phylogenetic distance,’’ NPD).
There was no significant relationship between S and
NPD (A; n ¼ 8, F ¼ 3.41, P ¼ 0.11) or between RY and
NPD (B; n ¼ 8, F ¼ 1.46, P ¼ 0.27). The dotted line in
panel (A) at S ¼ 1.0 and error bars are the same as in
Fig. 2A. In panel (B) RY values are natural logtransformed, standard errors approximated as in
Hedges et al. (1999), and the dotted line at ln(RY ) ¼
0 is the same as in Fig. 3.
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APPENDIX C
Data summaries from the
U.S. Environmental Protection Agency’s
National Lake Assessment (2007)
Fig. C1. Frequency histogram of the number of lakes
having a given green algal richness out of 1157 lakes in
the continental USA (U.S. Environmental Protection
Agency 2007). The vertical line at richness ¼ 17.84
represents the mean number of green algae species per
lake. The number of species used in this study, 8, falls
within one standard deviation of the mean (standard
deviation ¼ 11.51).
Table C1. Co-occurrence matrix of each pairwise combination of genera used in this experiment in continental
U.S. lakes (U.S. Environmental Protection Agency 2007). Numbers inside cells are the percentage of lakes out of
1157 in which the genera were observed together, where each lake was visited twice. Analysis was done using
Microsoft Access and Excel.
Percent (%) co-occurrence of listed genus with focal genus
Focal genus
Chlor.
Clos.
Cos.
Pand.
Scen.
Sel.
Staur.
Tet.
Chlorella
Closteriopsis
Cosmarium
Pandorina
Scenedesmus
Selenastrum
Staurastrum
Tetraedron
NA
1.64
NA
15.38
4.32
NA
0.95
0.52
1.56
NA
19.62
4.84
28.69
2.25
NA
3.03
2.85
10.20
1.38
12.88
NA
8.90
3.98
17.46
1.04
20.74
8.12
NA
9.85
2.51
11.32
0.00
16.42
3.28
9.08
NA
Notes: Empty cells are a mirror image of filled cells. ‘‘NA’’ denotes the ‘‘non-applicable’’ co-occurrence of a genus with itself.
Column subheadings are abbreviated genus names as listed fully under ‘‘Focal genus.’’
SUPPLEMENT
Data files used in the main text (Ecological Archives, http://dx.doi.org/10.1890/ES14-00502.1.sm).
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